[HTML][HTML] Diagnostic accuracy of the Finnish Diabetes Risk Score (FINDRISC) for undiagnosed T2DM in Peruvian population

A Bernabe-Ortiz, P Perel, JJ Miranda, L Smeeth - Primary care diabetes, 2018 - Elsevier
Aims To assess the diagnostic accuracy of the Finnish Diabetes Risk Score (FINDRISC) for
undiagnosed T2DM and to compare its performance with the Latin-American FINDRISC (LA …

Gestational diabetes mellitus risk score: a practical tool to predict gestational diabetes mellitus risk in Tanzania

AP Nombo, AW Mwanri, EM Brouwer-Brolsma… - Diabetes research and …, 2018 - Elsevier
Background Universal screening for hyperglycemia during pregnancy may be in-practical in
resource constrained countries. Therefore, the aim of this study was to develop a simple …

Risk assessment tools for detecting those with pre-diabetes: a systematic review

SR Barber, MJ Davies, K Khunti, LJ Gray - Diabetes research and clinical …, 2014 - Elsevier
Aim To describe and evaluate risk assessment tools which detect those with pre-diabetes
defined as either impaired glucose tolerance or impaired fasting glucose using an OGTT or …

Rule extraction from support vector machines using ensemble learning approach: an application for diagnosis of diabetes

L Han, S Luo, J Yu, L Pan… - IEEE journal of biomedical …, 2014 - ieeexplore.ieee.org
Diabetes mellitus is a chronic disease and a worldwide public health challenge. It has been
shown that 50-80% proportion of T2DM is undiagnosed. In this paper, support vector …

Comparison of machine-learning algorithms to build a predictive model for detecting undiagnosed diabetes-ELSA-Brasil: accuracy study

AR Olivera, V Roesler, C Iochpe, MI Schmidt… - Sao Paulo Medical …, 2017 - SciELO Brasil
ABSTRACT CONTEXT AND OBJECTIVE: Type 2 diabetes is a chronic disease associated
with a wide range of serious health complications that have a major impact on overall health …

[HTML][HTML] Type 2 diabetes mellitus screening and risk factors using decision tree: results of data mining

S Habibi, M Ahmadi, S Alizadeh - Global journal of health science, 2015 - ncbi.nlm.nih.gov
Objectives: The aim of this study was to examine a predictive model using features related to
the diabetes type 2 risk factors. Methods: The data were obtained from a database in a …

Diabetes in the Western Pacific Region—past, present and future

JCN Chan, NH Cho, N Tajima, J Shaw - Diabetes research and clinical …, 2014 - Elsevier
In the 2013 issue of the International Diabetes Federation (IDF) Diabetes Atlas, the
prevalence of diabetes in the Western Pacific (WP) Region was reported to be 8.6% in 2013 …

Translation and performance of the Finnish Diabetes Risk Score for detecting undiagnosed diabetes and dysglycaemia in the Indonesian population

MR Rokhman, B Arifin, Z Zulkarnain, S Satibi… - PLoS …, 2022 - journals.plos.org
A diabetes risk score cannot directly be translated and applied in different populations, and
its performance should be evaluated in the target population. This study aimed to translate …

Machine learning risk score for prediction of gestational diabetes in early pregnancy in Tianjin, China

H Liu, J Li, J Leng, H Wang, J Liu, W Li… - Diabetes/metabolism …, 2021 - Wiley Online Library
Aims This study aimed to develop a machine learning–based prediction model for
gestational diabetes mellitus (GDM) in early pregnancy in Chinese women. Materials and …

Performance of the finnish diabetes risk score and a simplified finnish diabetes risk score in a community-based, cross-sectional programme for screening of …

MA Salinero-Fort, C Burgos-Lunar, C Lahoz… - Plos one, 2016 - journals.plos.org
Aim To evaluate the performance of the Finnish Diabetes Risk Score (FINDRISC) and a
simplified FINDRISC score (MADRISC) in screening for undiagnosed type 2 diabetes …